Comments (11)
Thanks a lot !
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Hi, AFHQ-CAT dataset does not have the domain lables, therefore, it can not conduct the semi-supervised learning.
I am so sorry for the inconvenience. It should be changed into "python main.py --gpu 0 --dataset afhq_cat --output_k 10 --data_path '../data' --p_semi 0.0"
I will change ReadMe. Thank you for letting me know that!
from tunit.
Thanks for your answer.
I saw you used the animal faces dataset and FOOD-101 dataset.
I can find the name of the class name of Animal Faces in code,but I can not find the FOOD-101 class name
could you please provide the ten classes' names that used for FOOD-101 dataset?
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This source code is under the refactoring, so I provide the class names directly:
baby_back_ribs
beef_carpaccio
beignets
bibimbap
caesar_salad
clam_chowder
dumplings
edamame
spaghetti_bolognese
strawberry_shortcake
These are the file of the used classes in Food-101.
I copy and paste the folders and use [i for i in range(10)].
Then, give the directory of Food-10.
from tunit.
Hi,could you share the set about the Food-10 dataset?
Such as in your validation.py L52-61,you set this:
Parse images for average reference vector
x_each_cls = []
if args.dataset == 'animal_faces':
num_tmp_val = -50
elif args.dataset == 'ffhq':
num_tmp_val = -7000
elif args.dataset == 'lsun_car':
num_tmp_val = -10000
else:
num_tmp_val = 0
if I want to use food-10 to train,what should I set?
Thanks
from tunit.
The Food-10 dataset is basically the same as 'animal_faces' dataset. Therefore, you should change the conditions containing 'animal_faces' into a condition having 'food-10'.
For the above example, you should change to
if args.dataset in ['animal_faces', 'food-10']
'food-10' might be changed as you set.
from tunit.
ok~ got it~Thanks
from tunit.
If it is ok, I will upload the source code without refactoring but simply applied "food-10"
from tunit.
oh That's cool.
I will glad to see that~
Thanks again~
from tunit.
Please check "food_added" branch. I assume that you separated a folder only for food-10.
If you have any issues, feel free to tell me.
from tunit.
I got it~
Thank you very much~
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Related Issues (20)
- OOM of training summer2winter HOT 6
- Why the argumentation transform of the orginal image contains colorjitter HOT 6
- Seek the AnimalFaces Dataset HOT 2
- question about the animal faces dataset HOT 1
- FFHQ: IndexError list index out of range HOT 4
- Training on non-square images HOT 1
- It looks like the requirements.txt file needs to be modified. HOT 1
- About custom dataset HOT 1
- Validation Error? HOT 8
- About Food-10 dataset settings HOT 5
- Average style vectors? HOT 2
- Why updating the gradients of the guiding network C while training G? HOT 2
- Why the style encoder maps all the images to the same style code? HOT 7
- Can TUNIT do few-shot generation? HOT 4
- Training Discriminator vs Generator in TUNIT HOT 2
- pretarined food10 weights HOT 5
- I trained to 65 epochs and found an error:“fid_ema, fid_ema_mean is not defined” HOT 9
- FFHQ results HOT 1
- Own Dataset HOT 1
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